Research On Optimization Method Of Cloud Manufacturing Service Composition Based On E-CARGO Model

With the innovation of information technology and the commercialization of 5G technology,traditional manufacturing enterprises continue to transform and upgrade urgently for survival and development,and the concept of cloud manufacturing emerges as the times require.Cloud manufacturing is a new model of service-oriented,high-efficiency,lowconsumption and knowledge-based networked intelligent manufacturing.Cloud manufacturing can integrate manufacturing resources cross domain and cross regional,manage centrally and optimize intelligently the allocation of distributed manufacturing resources,so as to solve the problems of low utilization and sharing of manufacturing resources.Nowadays,with the more refined and specialized division of labor in the manufacturing industry,in order to improve the internal competitiveness,manufacturing enterprises usually choose to complete the manufacturing tasks in the cloud manufacturing scenario through the service composition of resources.However,the cloud platform contains a large number of service resources with the same or similar functions but different quality of service(Qo S).The key problem of cloud manufacturing service composition is to select the optimal composition from the massive service composition schemes.Therefore,this thesis proposes a cloud manufacturing service composition optimization method based on E-CARGO model.The main research work of this thesis is as follows:(1)Aiming at the collaborative problem in cloud manufacturing scenario,a role-based collaborative cloud manufacturing service composition optimization method is proposed.Firstly,the mapping relationship between service composition and E-CARGO model is established,and the E-CARGO model of cloud manufacturing service composition is constructed.Secondly,aiming at the uncertainty of Qo S,the dynamic quality of service is transformed into expectation,entropy and super entropy in cloud model,calculating the similarity between Qo S cloud models,then the qualification evaluation matrix is obtained.Finally,the role-based collaborative cloud manufacturing service composition problem is solved and the optimal service composition scheme is obtained.(2)Aiming at the problem of service conflict in cloud manufacturing scenario,a conflict aware service composition optimization method for cloud manufacturing is proposed.Firstly,the conflict aware cloud manufacturing service composition problem is abstracted as a role collaboration problem,and this problem is formally modeled based on the nine tuples element model of E-CARGO model.Secondly,the preference index system of users is established,combining the qualification evaluation matrix with the users' preference.Finally,the conflict aware cloud manufacturing service composition problem is solved and the optimal service composition scheme is obtained.(3)In order to verify the rationality and effectiveness of our proposed methods,IBM CPLEX optimization package is used to solve the cloud manufacturing service composition problem.The experimental results show that the cloud manufacturing service composition optimization methods based on E-CARGO model can effectively solve the service composition problem in the cloud manufacturing scenario.